Optimization & Theory
43,292 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Optimization (17,731)
Learning Theory (6,809)
Bayesian Inference (6,267)
Theory (5,579)
Statistical Learning (4,564)
Neural Network Optimization (4,155)
Stochastic Processes (2,948)
Stochastic Methods (1,283)
Loss Functions (1,220)
Distributed Learning (1,202)
Online Algorithms (1,013)
Statistics (822)
Generalization (376)
Information Theory (370)
Sample Complexity (282)
Sparse Optimization (241)
Game Theory (151)
Convex Optimization (132)
Optimal Transport (104)
Robust Optimization (84)
Distributed Optimization (73)
Approximation Algorithms (33)
Papers per year
1
14
29
44
31
52
189
195
212
235
352
382
457
787
816
828
1,066
1,391
1,913
3,012
3,646
4,303
4,450
5,357
6,155
5,854
1,521
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
On Stationary Point Convergence of PPO-Clip
ICLR 2024
On Statistical Learning Theory for Distributional Inputs
ICML 2024
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
NeurIPS 2024
On Tail Decay Rate Estimation of Loss Function Distributions
JMLR 2024
On the Ability of Developers' Training Data Preservation of Learnware
NeurIPS 2024
On the Actionability of Outcome Prediction
AAAI 2024
On the Adversarial Robustness of Benjamini Hochberg
NeurIPS 2024
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
AAAI 2024
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection
ICLR 2024
On the Asymptotic Distribution of the Minimum Empirical Risk
ICML 2024
On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization
EACL 2024
On the calibration of powerset speaker diarization models
Interspeech 2024
On the cohesion and separability of average-link for hierarchical agglomerative clustering
NeurIPS 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
ICML 2024
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
ICML 2024
On the Complexity of Identification in Linear Structural Causal Models
NeurIPS 2024
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
NeurIPS 2024
On the Computability of Robust PAC Learning
COLT 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing
JMLR 2024
On the Computational Benefit of Multimodal Learning
ALT 2024
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling
JMLR 2024
On the Computational Complexity of Plan Verification, (Bounded) Plan-Optimality Verification, and Bounded Plan Existence
AAAI 2024
On the Computational Complexity of Private High-dimensional Model Selection
NeurIPS 2024
On the Computational Landscape of Replicable Learning
NeurIPS 2024
On the Computation of Example-Based Abductive Explanations for Random Forests
IJCAI 2024